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Circadian dynamics of high frequency oscillations in patients with epilepsy

SYSNO ASEP	0472661
Document Type	C - Proceedings Paper (int. conf.)
R&D Document Type	Conference Paper
Title	Circadian dynamics of high frequency oscillations in patients with epilepsy
Author(s)	Balach, J. (CZ) Ježdík, P. (CZ) Janča, R. (CZ) Čmejla, R. (CZ) Kršek, P. (CZ) Marusič, P. (CZ) Jiruška, Přemysl (FGU-C)_{RID, ORCID, SAI}
Source Title	Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS. - Rome : SciTePress, 2016 - ISBN 978-989758170-0
Pages	s. 284-289
Number of pages	6 s.
Publication form	Online - E
Action	BIOSIGNALS 2016 - International Conference on Bio-Inspired Systems and Signal Processing /9./,Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016
Event date	21.02.2016 - 23.02.2016
VEvent location	Rome
Country	IT - Italy
Event type	WRD
Language	eng - English
Country	IT - Italy
Keywords	circadian rhythms ; epilepsy ; high-frequency oscillations ; intracerebral EEG ; seizure onset zone
Subject RIV	FH - Neurology
R&D Projects	NT14489 GA MZd - Ministry of Health (MZ)
	GA14-02634S GA ČR - Czech Science Foundation (CSF)
	NV15-29835A GA MZd - Ministry of Health (MZ)
Institutional support	FGU-C - RVO:67985823
EID SCOPUS	84969180504
DOI	10.5220/0005827602840289
Annotation	High frequency oscillations (HFOs) are novel biomarker of epileptogenic tissue. HFOs are currently used to localize the seizure generating areas of the brain, delineate the resection and to monitor the disease activity. It is well established that spatiotemporal dynamics of HFOs can be modified by sleep-wake cycle. In this study we aimed to evaluate in detail circadian and ultradian changes in HFO dynamics using techniques of automatic HFO detection. For this purpose we have developed and implemented novel algorithm to automatic detection and analysis of HFOs in long-term intracranial recordings of six patients. In 5/6 patients HFO rates significantly increased during NREM sleep. The largest NREM related increase in HFO rates were observed in brain areas which spatially overlapped with seizure onset zone. Analysis of long-term recording revealed existence of ultradian changes in HFO dynamics. This study demonstrated reliability of automatic HFO detection in the analysis of long-term intracranial recordings in humans. Obtained results can foster practical implementation of automatic HFO detecting algorithms into presurgical examination, dramatically decrease human labour and increase the information yield of HFOs.
Workplace	Institute of Physiology
Contact	Lucie Trajhanová, lucie.trajhanova@fgu.cas.cz, Tel.: 241 062 400
Year of Publishing	2017

Number of the records: 1